sp
/
tempest
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
Browse Source

Scaling the rating of an observation with the current resolution.

tempestpy_adaptions
Tim Quatmann 5 years ago
parent
c2ddea1480
commit
c3847d05af
2 changed files with 13 additions and 9 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 16
      src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.cpp
  2. 4
      src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.h

16
src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.cpp
View File

@ -264,21 +264,23 @@ namespace storm {
* Here, 0 means a bad approximation and 1 means a good approximation.
*/
template<typename PomdpModelType, typename BeliefValueType>
typename ApproximatePOMDPModelchecker<PomdpModelType, BeliefValueType>::ValueType ApproximatePOMDPModelchecker<PomdpModelType, BeliefValueType>::rateObservation(typename ExplorerType::SuccessorObservationInformation const& info) {
typename ApproximatePOMDPModelchecker<PomdpModelType, BeliefValueType>::ValueType ApproximatePOMDPModelchecker<PomdpModelType, BeliefValueType>::rateObservation(typename ExplorerType::SuccessorObservationInformation const& info, uint64_t const& observationResolution, uint64_t const& maxResolution) {
auto n = storm::utility::convertNumber<ValueType>(info.successorWithObsCount);
auto one = storm::utility::one<ValueType>();
// Create the actual rating for this observation at this choice from the given info
// Create the rating for this observation at this choice from the given info
ValueType obsChoiceRating = info.maxProbabilityToSuccessorWithObs / info.observationProbability;
// At this point, obsRating is the largest triangulation weight (which ranges from 1/n to 1
// Normalize the rating so that it ranges from 0 to 1, where
// 0 means that the actual belief lies in the middle of the triangulating simplex (i.e. a "bad" approximation) and 1 means that the belief is precisely approximated.
obsChoiceRating = (obsChoiceRating * n - one) / (n - one);
// Scale the ratings with the resolutions, so that low resolutions get a lower rating (and are thus more likely to be refined)
obsChoiceRating *= storm::utility::convertNumber<ValueType>(observationResolution) / storm::utility::convertNumber<ValueType>(maxResolution);
return obsChoiceRating;
}
template<typename PomdpModelType, typename BeliefValueType>
std::vector<typename ApproximatePOMDPModelchecker<PomdpModelType, BeliefValueType>::ValueType> ApproximatePOMDPModelchecker<PomdpModelType, BeliefValueType>::getObservationRatings(std::shared_ptr<ExplorerType> const& overApproximation) {
std::vector<typename ApproximatePOMDPModelchecker<PomdpModelType, BeliefValueType>::ValueType> ApproximatePOMDPModelchecker<PomdpModelType, BeliefValueType>::getObservationRatings(std::shared_ptr<ExplorerType> const& overApproximation, std::vector<uint64_t> const& observationResolutionVector, uint64_t const& maxResolution) {
uint64_t numMdpChoices = overApproximation->getExploredMdp()->getNumberOfChoices();
std::vector<ValueType> resultingRatings(pomdp.getNrObservations(), storm::utility::one<ValueType>());
@ -289,7 +291,7 @@ namespace storm {
overApproximation->gatherSuccessorObservationInformationAtMdpChoice(mdpChoice, gatheredSuccessorObservations);
for (auto const& obsInfo : gatheredSuccessorObservations) {
auto const& obs = obsInfo.first;
ValueType obsChoiceRating = rateObservation(obsInfo.second);
ValueType obsChoiceRating = rateObservation(obsInfo.second, observationResolutionVector[obs], maxResolution);
// The rating of the observation will be the minimum over all choice-based observation ratings
resultingRatings[obs] = std::min(resultingRatings[obs], obsChoiceRating);
@ -303,6 +305,8 @@ namespace storm {
STORM_LOG_ASSERT(!refine || refinementAggressiveness != nullptr, "Refinement enabled but no aggressiveness given");
STORM_LOG_ASSERT(!refine || *refinementAggressiveness >= storm::utility::zero<ValueType>(), "Can not refine with negative aggressiveness.");
STORM_LOG_ASSERT(!refine || *refinementAggressiveness <= storm::utility::one<ValueType>(), "Refinement with aggressiveness > 1 is invalid.");
uint64_t maxResolution = *std::max_element(observationResolutionVector.begin(), observationResolutionVector.end());
STORM_LOG_INFO("Refining with maximal resolution " << maxResolution << ".");
statistics.overApproximationBuildTime.start();
storm::storage::BitVector refinedObservations;
@ -315,7 +319,7 @@ namespace storm {
}
} else {
// If we refine the existing overApproximation, we need to find out which observation resolutions need refinement.
auto obsRatings = getObservationRatings(overApproximation);
auto obsRatings = getObservationRatings(overApproximation, observationResolutionVector, maxResolution);
ValueType minRating = *std::min_element(obsRatings.begin(), obsRatings.end());
// Potentially increase the aggressiveness so that at least one observation actually gets refinement.
*refinementAggressiveness = std::max(minRating, *refinementAggressiveness);
@ -356,7 +360,7 @@ namespace storm {
overApproximation->gatherSuccessorObservationInformationAtCurrentState(action, gatheredSuccessorObservations);
for (auto const& obsInfo : gatheredSuccessorObservations) {
if (refinedObservations.get(obsInfo.first)) {
ValueType obsRating = rateObservation(obsInfo.second);
ValueType obsRating = rateObservation(obsInfo.second, observationResolutionVector[obsInfo.first], maxResolution);
stateActionRating = std::min(stateActionRating, obsRating);
}
}

4
src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.h
View File

@ -84,9 +84,9 @@ namespace storm {
*/
void buildUnderApproximation(std::set<uint32_t> const &targetObservations, bool min, bool computeRewards, uint64_t maxStateCount, std::shared_ptr<BeliefManagerType>& beliefManager, std::shared_ptr<ExplorerType>& underApproximation);
ValueType rateObservation(typename ExplorerType::SuccessorObservationInformation const& info);
ValueType rateObservation(typename ExplorerType::SuccessorObservationInformation const& info, uint64_t const& observationResolution, uint64_t const& maxResolution);
std::vector<ValueType> getObservationRatings(std::shared_ptr<ExplorerType> const& overApproximation);
std::vector<ValueType> getObservationRatings(std::shared_ptr<ExplorerType> const& overApproximation, std::vector<uint64_t> const& observationResolutionVector, uint64_t const& maxResolution);
struct Statistics {
Statistics();
Write Preview
Loading…
Cancel
Save